With the rapidly evolving technology of the smart grid, hybrid (including plug-in hybrid) and plug-in electric vehicles (xEVs), rechargeable batteries have emerged as the most prominent electrochemical energy source. Electrochemical energy is the field of energy technology concerned with electrochemical methods of energy conversion and energy storage. Electrochemical energy conversion devices (e.g., fuel cells) generate electricity by converting the chemical energy from a fuel (e.g., hydrogen) through a chemical reaction with an oxidizing agent. Although many experts believe electrochemical conversion devices, such as fuel cells, will eventually replace rechargeable batteries as the most-used electrochemical energy device, electrochemical conversion devices are currently not economically feasible, and may not be for decades. Unlike electrochemical energy conversion devices, electrochemical energy storage devices (e.g., rechargeable batteries and supercapacitors) do not require a fuel supply, but must be periodically recharged in order to supply electricity. Although supercapacitors (aka, ultracapacitors) require much less time to charge than rechargeable batteries, rechargeable batteries store and supply far more energy, and are thus the most prominent electrochemical energy device in use today.
Smart grid and EV systems typically include management systems that utilize various sensors to monitor and control the operational state of an electrochemical energy system. For example, a conventional battery management system (BMS) is often utilized to process sensor information received from current, voltage and temperature sensors connected to multiple rechargeable batteries at different battery cell, battery module, and battery pack levels. The sensor data is processed to determine the condition of the battery system expressed by terms like (but not limited to) state-of-charge (SOC), -power (SOP), -health (SOH), capacity, impedance, structural integrity (electrode cracking and delamination), cell packaging and sealing, terminal voltage, temperature, pressure and strain. By processing the sensor data and initiating appropriate actions, the BMS not only controls the operational conditions of the battery to prolong its life and guarantee its safety (e.g., by disconnecting a battery cell to prevent the uncontrolled release of concentrated energy), but also provides accurate estimation of the SOC and SOH for energy management modules in the smart grid and xEVs.
Although conventional BMS approaches provided acceptable SOX information for conventional uses in portable electronics, there is a growing need for a more accurate and reliable BMS approach for today's smart grid and xEV systems. For example, accurate SOX information is very important in EV systems so that the BMS can control and utilize a pack within its true safe limits of operation to avoid degradation or failure. These operational limits depend on environmental conditions, age, and usage. It can also enable an xEV driver to know how much longer a vehicle will operate in electric mode before recharging and/or servicing. Current methods for determining SOC information in xEV systems rely on voltage and current measurements; voltage measurements can be “flat” (i.e., relatively unchanging) at certain intermediate charge levels. In addition, the correlation between voltage and SOC can change as cells age. These factors can lead to inaccurate SOC estimates. Similarly, conventional BMS systems typically determine a battery's SOH by way of estimating capacity drops, detecting unusual temperature, current and voltage changes. Although this approach may provide useful information near the end of a battery's lifetime (i.e., by detecting battery failure), it typically is not useful at predicting failure in advance, preventing degradation, or for tracking cell aging. Moreover, because rechargeable batteries are used in increasingly challenging environments, are required to provide greater power and energy densities, and are expected to have longer useful lifetimes, it is becoming even more difficult to generate reliable and accurate SOX information using conventional BMS methodologies.
Therefore, there is a clear need for an improved electrochemical energy device management system that employs improved methodologies capable of providing accurate SOC information during the entire charge cycle of the device, and capable of providing accurate SOP and SOH information throughout the device's operating lifetime. One way to provide improved SOX information is by way of monitoring internal battery phenomena such as the transport of charged and neutral species, current conduction, fluid flow, heat transfer, chemical reactions (including parasitic reactions) at the electrode surfaces, gas formation, material balance and phase transition, and the intercalation of ionic species into porous electrodes with associated momentum transfer. For example, in electrochemical energy devices that utilize intercalation compounds (guest species) to store energy, such as a Li-ion rechargeable batteries or some supercapacitors, the electrode material typically undergoes crystalline structure “stage” changes during charging and discharging events (operations). These crystalline structure “stage” changes occur because the electrode material expands or contracts, respectively, as it accepts ions during charging, or loses (withdraws) ions during discharging. Intercalation stage transition points are repeatable, detectable events that occur within the electrode material with respect to charge/discharge states, and can be used to determine current (i.e., point-in-time) ion concentration levels within the electrode material. For example, certain graphite electrodes undergo five distinct crystalline structural changes over a charge cycle, as illustrated in FIG. 17, ranging from Stage 1 (fully charged) to Stage 5 (fully discharged).
Although the intercalation stage change phenomena can provide highly useful information for purposes of monitoring the SOX of an electrochemical energy storage device, the intercalation stage transition points cannot be measured directly by conventional methods like voltage, current and temperature measurements during runtime (i.e., during normal operating conditions), and existing methodologies require expensive equipment suitable only for laboratory settings. For example, currently identification of intercalation stages is performed primarily by slow scan rate cyclic voltammetry (SSCV), and potentiostatic intermittent titration (PITT) and electrochemical impedance spectroscopy (EIS) are also conducted in order to study the potentiodynamic behavior of batteries that are correlated to the intercalation stages. EIS provides a conventional approach for battery SOH estimation using intercalation stage information, but requires extensive prior calibration in the “healthy” condition, and also requires the battery to be in electrochemical equilibrium, and therefore is unsuitable for runtime monitoring. X-ray diffractometry and Fourier transform infrared (FTIR) spectroscopy are used in order to follow structural and surface chemical changes of battery electrodes under cycling, and Raman spectroscopy and atomic force microscopy (AFM) are also used for the structural characterization of materials used as electrodes in rechargeable lithium batteries. Other approaches for laboratory-level characterizations of internal cell state for model validation have included neutron radiography and optical microscopy in specially designed cells with quartz viewing windows. However, none of these methodologies are feasible outside a laboratory setting for use in full-time commercial applications, for example, such as monitoring the SOC and SOH of rechargeable batteries utilized to power xEVs.
What is needed is a low-cost, reliable system and method for detecting intercalation stage transition points of an electrode material within an electrochemical energy storage device. In particular, what is needed is a practical management system and management method for accurately determining the SOX (e.g., SOC and SOH) of electrochemical energy storage devices, such as rechargeable batteries utilized to power EVs, by way of measuring and recording such intercalation stage transition points.